Supply chain planning, which comprises the logistical plan of an in-house supply chain, is essential to the success of many of today""s manufacturing firms. Most manufacturing firms rely on supply chain planning in some form to ensure the timely delivery of products in response to customer demands. Typically, supply chain planning is hierarchical in nature, extending from distribution and production planning driven by customer orders, to materials and capacity requirements planning, to shop floor scheduling, manufacturing execution, and deployment of products. Supply chain planning ensures the smooth functioning of different aspects of production, from the ready supply of components to meet production demands to the timely transportation of finished goods from the factory to the customer.
The modern supply chain often encompasses a vast array of data. The planning applications that create and dynamically revise plans in the supply chain in response to changing demands and capacity require rapid access to data concerning the flow of materials through the supply chain. The efficient operation of the supply chain depends upon the ability of the various plans to adjust to changes, and the way in which the required data is stored determines the ease with which it can be accessed.
In the conventional relational model, supply chain data is stored in multiple relational database tables. If a parameter of a manufacturing order is changed, all of the aspects of the supply chain affected by such change must be re-calculated using the relational tables. Before a planning algorithm can change the date and/or quantity of a manufacturing order in response to changing capacities, for example, it must take into account the effect that the date and/or quantity change will have on other production and sales orders. Such a calculation is very complex, and requires that the algorithm have access to data concerning all the other orders, materials and resources that would be affected by the change. That information is not readily accessible in the conventional model, and instead must be calculated by tracing through relational database tables. Such calculations are cumbersome and delay planning functions unnecessarily.
There is therefore a need for all data relevant to supply chain planning to be stored in an efficient manner which reflects the progress of materials and orders along the supply chain. There is also a need for such data to be made available to planning algorithms in the most efficient and usable manner possible so as to reduce drastically the runtime of the planning functions.
The present invention relates to a data model for storing objects that are relevant for planning the logistical processes along the entire supply chain of a company.
It is an object of the invention to store manufacturing process data so as to provide planning algorithms and applications programs with the most efficient access possible to the data that they require.
It is a further object of this invention to store the data in a logical manner that reflects the progress of materials and orders along the supply chain.
It is a further object of this invention to define discrete data elements representing individual working steps in the production process, and to store the relationships between said elements.
It is a further object of this invention that specific information about each working step is linked with those data elements, including the start time, finish time, and the resources upon which the working step is performed or alternatively may be performed.
It is a further object of the invention to organize groups of working steps in the manufacturing process as objects that can be accessed by planning algorithms, and to store the relationships between said groups of working steps.
It is a further object of this invention to allow a planning algorithm efficient access to any organized group of working steps in the production process by providing a database table whereby each of the groups of working steps is referenced to its location in the data structure.
It is a further object of this invention to allow a planning algorithm efficient access to the working step performed by a given resource at a specific time, by providing a database table whereby the dates and times of all working steps performed by each resource are referenced to that resource.
It is a further object of the invention to allow a planning algorithm to have efficient access to organized groups of working steps involved in creating or consuming a specific material, by providing a database table whereby information identifying the material is referenced to the input or output of each such organized group of working steps.
In accordance with these and other objects, a data structure is defined whereby individual working steps in the production process are defined as activities, and organized groups of such activities are defined as orders. Activities are allocated to no more than one resource, if any, and contain information concerning the start and finish time for the activity, any resource on which the activity is currently scheduled, and a list of alternative resources, if any. Activities representing a time calculation only are not required to correspond to a resource. Activities are linked to each other via auxiliary objects, which contain information concerning the minimum and maximum time between activities. Orders may contain input and/or output interface nodes, representing the materials consumed and produced by activities within the order. An output interface node representing a quantity of material created from one order is linked via an auxiliary object to respective input interface node or nodes from other orders that require that material. Order anchors are defined whereby a planning algorithm can easily reference an order in the data structure by its order number in a database table. Planning object anchors allow the planning algorithm to access all the orders for a given material, and resource anchors permit access to all activities scheduled for that resource.